Capacity planning involves the identification of hardware and software configurations that are best suited to meet the needs of a telecommunications network. Capacity planning requires an understanding of service levels, resource usage, etc. to align capacity requirements with business demands. One of the major goals of capacity planning is to ensure that the business service-level objectives are met. However, multiple services are competing for the same forward and return path spectrum. Thus, in today's competitive environment, network quality and performance reliability are as important as the breadth of services offered.
A data model representing the telecommunications network is often used in management and capacity planning. System planners use a variety of analytical tools, formulas and techniques to implement a capacity planning methodology. For example, some of the issues involved in capacity planning include defining capacity areas, capacity variables and performance models. Models are used to ensure planning decisions are based on sound information. These models are calibrated and validated to ensure that the models accurately reflect the actual operation of the system. Identifying the relationship between Business Metrics of Interest (BMIs) and available system performance metrics is critical to accurate models and forecasts. BMIs represent the real world transactions that drive a business workload's resource consumption. System planners and network managers base their decisions on the analysis of the model in an attempt to optimized network configurations and plan network evolution.
However, there are often competing interests in determining what capacity plan modifications to implement. A difficult, but important, component associated with capacity planning for cable, Internet and other communications companies is determining how much bandwidth is needed. Typically there are three curves involved in determining how much capacity is needed on a given network.
The demand curve is almost an asymptotic curve. However, a point may be reached the demand curve goes to infinity. The retail curve focuses on the product being sold to the users in terms of the growth of the service being provided and is generally linear. Somewhere between the retail and demand curve is the user experience curve that illustrates a measure of the user experience. The user experience curve defines, at any point in time, how much capacity is available to keep customers satisfied. The closer capacity approaches the demand line, the better bandwidth is provided to the user. The closer you get to the retail line, the less expensive the service is, but leaves customers feeling less satisfied about the experience.
Previously methods for planning capacity requirements focus on access devices and determining how much bandwidth a group of users are consuming. Projections are made regarding how much bandwidth is the group of users looking for to satisfy their downstream consumption and how much bandwidth are users looking for to meet upstream consumption needs.
However, these methods are characterized as a top-down view of capacity planning. Necessarily, top-down capacity planning relies on a very macro level. Thus, the fine grain details that are unique to demographics, to age groups, etc. are missed.